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The field of computational pathology has witnessed remarkable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders.
Systematic analysis of breast cancer morphology uncovers stromal features associated with survival
Beck, A. H. et al · 2011
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.-Y. et al · 2014
Earlier work this paper cites.
Image analysis and machine learning in digital pathology: Challenges and opportunities
Madabhushi, A. & Lee, G · 2016
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Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
Ehteshami Bejnordi, B. et al · 2017
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Attention Is All You Need
Vaswani, A. et al · 2017
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Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
Coudray, N. et al · 2018
Earlier work this paper cites.
Predicting cancer outcomes from histology and genomics using convolutional networks
Mobadersany, P. et al · 2018
Earlier work this paper cites.
Radiology objects in context (roco): a multimodal image dataset
Pelka, O., Koitka, S., Rückert, J., Nensa, F. & Friedrich, C. M · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training (2018)
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I. et al · 2018
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Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V. & Madabhushi, A · 2019
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Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the digital pathology association
Abels, E. et al · 2019
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Development and validation of a deep learning algorithm for improving gleason scoring of prostate cancer
Nagpal, K. et al · 2019
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Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Campanella, G. et al · 2019
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Deep learning-based classification of mesothelioma improves prediction of patient outcome
Courtiol, P. et al · 2019
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Similar image search for histopathology: Smily
Hegde, N. et al · 2019
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Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
Graham, S. et al · 2019
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Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Lu, J., Batra, D., Parikh, D. & Lee, S · 2019
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Language models are unsupervised multitask learners
Radford, A. et al · 2019
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Publicly available clinical bert embeddings
Alsentzer, E. et al · 2019
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Automated deep-learning system for gleason grading of prostate cancer using biopsies: a diagnostic study
Bulten, W. et al · 2020
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A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
Lu, C. et al · 2020
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Yottixel–an image search engine for large archives of histopathology whole slide images
Kalra, S. et al · 2020
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Pan-cancer image-based detection of clinically actionable genetic alterations
Kather, J. N. et al · 2020
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Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis
Fu, Y. et al · 2020
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A simple framework for contrastive learning of visual representations
Chen, T., Kornblith, S., Norouzi, M. & Hinton, G · 2020
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Momentum contrast for unsupervised visual representation learning
He, K., Fan, H., Wu, Y., Xie, S. & Girshick, R · 2020
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Unicoder-vl: A universal encoder for vision and language by cross-modal pre-training
Li, G., Duan, N., Fang, Y., Gong, M. & Jiang, D · 2020
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Uniter: Universal image-text representation learning
Chen, Y.-C. et al · 2020
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Oscar: Object-semantics aligned pre-training for vision-language tasks
Li, X. et al · 2020
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Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media
Schaumberg, A. J. et al · 2020
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Evaluating and interpreting caption prediction for histopathology images
Zhang, R., Weber, C., Grossman, R. & Khan, A. A · 2020
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Language models are few-shot learners
Brown, T. et al · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C. et al · 2020
Earlier work this paper cites.
Artificial intelligence and computational pathology
Cui, M. & Zhang, D. Y · 2021
Earlier work this paper cites.
Data-efficient and weakly supervised computational pathology on whole-slide images
Lu, M. Y. et al · 2021
Earlier work this paper cites.
Ai-based pathology predicts origins for cancers of unknown primary
Lu, M. Y. et al · 2021
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Emerging properties in self-supervised vision transformers
Caron, M. et al · 2021
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Image bert pre-training with online tokenizer
Zhou, J. et al · 2021
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Learning transferable visual models from natural language supervision
Radford, A. et al · 2021
Earlier work this paper cites.
Scaling up visual and vision-language representation learning with noisy text supervision
Jia, C. et al · 2021
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Vinvl: Revisiting visual representations in vision-language models
Zhang, P. et al · 2021
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Align before fuse: Vision and language representation learning with momentum distillation
Li, J. et al · 2021
Earlier work this paper cites.
Multiple instance captioning: Learning representations from histopathology textbooks and articles
Gamper, J. & Rajpoot, N · 2021
Cited alongside, same era.
Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition
Huang, S.-C., Shen, L., Lungren, M. P. & Yeung, S · 2021
Cited alongside, same era.
Eslami, S., de Melo, G. & Meinel, C · 2021
Cited alongside, same era.
Towards visual question answering on pathology images
He, X · 2021
Cited alongside, same era.
Perceiver: General perception with iterative attention
Jaegle, A. et al · 2021
Cited alongside, same era.
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
Saldanha, O. L. et al · 2023
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Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study
Wagner, S. J. et al · 2023
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Multi-site cross-organ calibrated deep learning (muscld): Automated diagnosis of non-melanoma skin cancer
Zhou, Y. et al · 2023
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One model is all you need: multi-task learning enables simultaneous histology image segmentation and classification
Graham, S. et al · 2023
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Dinov2: Learning robust visual features without supervision
Oquab, M. et al · 2023
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Shmatko, A., Ghaffari Laleh, N., Gerstung, M. & Kather, J. N · 2022
Cited alongside, same era.
The future of artificial intelligence in digital pathology–results of a survey across stakeholder groups
Heinz, C. N., Echle, A., Foersch, S., Bychkov, A. & Kather, J. N · 2022
Cited alongside, same era.
Artificial intelligence for multimodal data integration in oncology
Lipkova, J. et al · 2022
Cited alongside, same era.
Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings
Huang, S.-C. et al · 2022
Cited alongside, same era.
Pan-cancer integrative histology-genomic analysis via multimodal deep learning
Chen, R. J. et al · 2022
Cited alongside, same era.
Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning
Lee, Y., Park, J., Oh, S. et al · 2022
Cited alongside, same era.
Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer
Boehm, K. M. et al · 2022
Cited alongside, same era.
Chen, R. J. et al · 2023
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Domain-specific optimization and diverse evaluation of self-supervised models for histopathology
Lai, J. et al · 2023
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Virchow: A million-slide digital pathology foundation model
Vorontsov, E. et al · 2023
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Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
Azizi, S. et al · 2023
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Campanella, G. et al · 2023
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Benchmarking self-supervised learning on diverse pathology datasets
Kang, M., Song, H., Park, S., Yoo, D. & Pereira, S · 2023
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Leveraging medical twitter to build a visual–language foundation model for pathology ai
Huang, Z., Bianchi, F., Yuksekgonul, M., Montine, T. & Zou, J · 2023
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Large-scale domain-specific pretraining for biomedical vision-language processing
Zhang, S. et al · 2023
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Quilt-1m: One million image-text pairs for histopathology
Ikezogwo, W. O. et al · 2023
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PMC-CLIP: Contrastive language-image pre-training using biomedical documents
Lin, W. et al · 2023
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Towards a visual-language foundation model for computational pathology
Lu, M. Y. et al · 2023
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Visual language pretrained multiple instance zero-shot transfer for histopathology images
Lu, M. Y. et al · 2023
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Pathnarratives: Data annotation for pathological human-ai collaborative diagnosis
Zhang, H. et al · 2023
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Llama: Open and efficient foundation language models
Touvron, H. et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H. et al · 2023
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A survey of large language models
Zhao, W. X. et al · 2023
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Anil, R. et al · 2023
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Med-flamingo: a multimodal medical few-shot learner
Moor, M. et al · 2023
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Multimodal foundation models: From specialists to general-purpose assistants
Li, C. et al · 2023
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Visual instruction tuning
Liu, H., Li, C., Wu, Q. & Lee, Y. J · 2023
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Foundation models for generalist medical artificial intelligence
Moor, M. et al · 2023
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Sparks of artificial general intelligence: Early experiments with gpt-4
Bubeck, S. et al · 2023
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Towards expert-level medical question answering with large language models
Singhal, K. et al · 2023
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Towards generalist biomedical ai
Tu, T. et al · 2023
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Health system-scale language models are all-purpose prediction engines
Jiang, L. Y. et al · 2023
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Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum
Ayers, J. W. et al · 2023
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Can generalist foundation models outcompete special-purpose tuning? case study in medicine (2023)
Nori, H. et al · 2023
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Capabilities of gpt-4 on medical challenge problems
Nori, H., King, N., McKinney, S. M., Carignan, D. & Horvitz, E · 2023
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Accuracy of a vision-language model on challenging medical cases
Buckley, T., Diao, J. A., Rodman, A. & Manrai, A. K · 2023
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Pathasst: Redefining pathology through generative foundation ai assistant for pathology
Sun, Y. et al · 2023
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Li, C. et al · 2023
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Wu, C. et al · 2023
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Bridging bytes and biopsies: A comparative analysis of chatgpt and histopathologists in pathology diagnosis and collaborative potential
Oon, M. L., Syn, N. L., Tan, C. L., Tan, K.-B. & Ng, S.-B · 2023
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Large language models encode clinical knowledge
Singhal, K. et al · 2023
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Improved baselines with visual instruction tuning
Liu, H., Li, C., Li, Y. & Lee, Y. J · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality (2023)
Chiang, W.-L. et al · 2023
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What matters in training a gpt4-style language model with multimodal inputs?
Zeng, Y. et al · 2023
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